Tom graduated from the University of Oxford in 2015 with a BA in Economics and Management, and completed an MSc in Financial Engineering at the University of Birmingham in 2018. He spent the intervening years working for an insurance company as an actuarial trainee, which is where Tom really began to find his passion for applied maths generally, and probability theory in particular. Since then, he has also developed an interest in numerical analysis. As part of his MSc, Tom completed a project in which he implemented and benchmarked, using C++, a Monte Carlo-based method for calculating guaranteed confidence intervals for means of random variables. In his spare time, Tom enjoys reading and programming, and is also (slowly) learning how to cook.

Research project title:
Monte Carlo Methods for Particle Systems and the Neutron Transport Equation

Supervisor(s):
Alex Cox, Andreas Kyprianou

Project description:
The flux of neutrons in a nuclear reactor has traditionally been modelled and understood using deterministic numerical methods. Recent probabilistic treatments have justified the use of stochastic processes to model neutron flux; Monte Carlo methods can then be used to simulate these processes. However, different Monte Carlo estimators suffer from various pitfalls: some techniques have a high per-iteration cost and are very difficult to parallelise, while other estimators have lower cost per individual simulation but an unacceptably high variance. Tom’s research project will investigate ways in which the neutron particle system may be simulated, using Monte Carlo algorithms which are both efficient and amenable to parallelisation. He also hopes to establish convergence, and other theoretical properties, of the resulting algorithms.